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Operational Risk Assesement Tools for Quality Management in Banking Services

  • Alina Mihaela Dima


    (The Bucharest Academy of Economic Studies, Romania)

Among all the different types of risks that can affect financial companies, the operational risk can be the most devastating and the most difficult to anticipate. The management of operational risk is a key component of financial and risk management discipline that drives net income results, 2capital management and customer satisfaction. The present paper contains a statistical analysis in order to determine the number of operational errors as quality based services determinants, depending on the number of transactions performed at the branch unit level. Regression model applied to a sample of 418 branches of a major Romanian bank is used to guide the decision taken by the bank, consistent with its priorities of minimizing the risk and enlarging the customer base ensuring high quality services. The analyisis reveals that the model can predict the quality of the transactions based on the number of operational errors. Under Basel II, this could be a very helpful instrument for banks in order to adjust the capital requirement to the losses due to operational errors, predicted by the model.

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Article provided by Academy of Economic Studies - Bucharest, Romania in its journal The AMFITEATRU ECONOMIC journal.

Volume (Year): 11 (2009)
Issue (Month): 26 (June)
Pages: 364-372

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Handle: RePEc:aes:amfeco:v:11:y:2009:i:26:p:364-373
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  1. Carolyn Currie, 2005. "A Test of the Strategic Effect of Basel II Operational Risk Requirements on Banks," Working Paper Series 141, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
  2. Carolyn Currie, 2004. "Basel II and Operational Risk - Overview of Key Concerns," Working Paper Series 134, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
  3. Healy, Paul M. & Palepu, Krishna G., 2001. "Information asymmetry, corporate disclosure, and the capital markets: A review of the empirical disclosure literature," Journal of Accounting and Economics, Elsevier, vol. 31(1-3), pages 405-440, September.
  4. Robert Hauswald & Robert Marquez, 2006. "Competition and Strategic Information Acquisition in Credit Markets," Review of Financial Studies, Society for Financial Studies, vol. 19(3), pages 967-1000.
  5. Galindo, J & Tamayo, P, 2000. "Credit Risk Assessment Using Statistical and Machine Learning: Basic Methodology and Risk Modeling Applications," Computational Economics, Society for Computational Economics, vol. 15(1-2), pages 107-43, April.
  6. Simon Kwan & Robert Eisenbeis, 1997. "Bank Risk, Capitalization, and Operating Efficiency," Journal of Financial Services Research, Springer, vol. 12(2), pages 117-131, October.
  7. Kenneth Daniels & Gabriel Ramirez, 2008. "Information, Credit Risk, Lender Specialization and Loan Pricing: Evidence from the DIP Financing Market," Journal of Financial Services Research, Springer, vol. 34(1), pages 35-59, August.
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